| | --- |
| | license: mit |
| | base_model: tangminhanh/ops_tg |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - accuracy |
| | - f1 |
| | - precision |
| | - recall |
| | model-index: |
| | - name: ops_cate |
| | results: [] |
| | --- |
| | |
| | <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| | should probably proofread and complete it, then remove this comment. --> |
| |
|
| | # ops_cate |
| | |
| | This model is a fine-tuned version of [tangminhanh/ops_tg](https://huggingface.co/tangminhanh/ops_tg) on the None dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.0637 |
| | - Accuracy: 0.7300 |
| | - F1: 0.7824 |
| | - Precision: 0.8357 |
| | - Recall: 0.7355 |
| | |
| | ## Model description |
| | |
| | More information needed |
| | |
| | ## Intended uses & limitations |
| | |
| | More information needed |
| | |
| | ## Training and evaluation data |
| | |
| | More information needed |
| | |
| | ## Training procedure |
| | |
| | ### Training hyperparameters |
| | |
| | The following hyperparameters were used during training: |
| | - learning_rate: 2e-05 |
| | - train_batch_size: 32 |
| | - eval_batch_size: 64 |
| | - seed: 42 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - num_epochs: 7 |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | |
| | |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:| |
| | | No log | 1.0 | 121 | 0.1398 | 0.1661 | 0.2807 | 0.9302 | 0.1653 | |
| | | No log | 2.0 | 242 | 0.1019 | 0.4891 | 0.6180 | 0.8375 | 0.4897 | |
| | | No log | 3.0 | 363 | 0.0805 | 0.6532 | 0.7296 | 0.8234 | 0.6550 | |
| | | No log | 4.0 | 484 | 0.0711 | 0.6854 | 0.7523 | 0.8313 | 0.6870 | |
| | | 0.1434 | 5.0 | 605 | 0.0655 | 0.7072 | 0.7697 | 0.8409 | 0.7097 | |
| | | 0.1434 | 6.0 | 726 | 0.0645 | 0.7227 | 0.7742 | 0.8316 | 0.7242 | |
| | | 0.1434 | 7.0 | 847 | 0.0637 | 0.7300 | 0.7824 | 0.8357 | 0.7355 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.42.4 |
| | - Pytorch 2.3.1+cu121 |
| | - Datasets 2.20.0 |
| | - Tokenizers 0.19.1 |
| | |
